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Towards professionally user-adaptive large medical image transmission processing in mobile telemedicine systems

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Abstract

To effectively and efficiently reduce the transmission costs of large medical image in (mobile) telemedicine systems, we design and implement a professionally user-adaptive large medical image transmission method called UMIT. Before transmission, a preprocessing step is first conducted to obtain the optimal image block (IB) replicas based on the users’ professional preference model and the network bandwidth at a master node. After that, the candidate IBs are transmitted via slave nodes according to the transmission priorities. Finally, the IBs can be reconstructed and displayed at the users’ devices. The proposed method includes three enabling techniques: (1) user’s preference degree derivation of the medically useful areas, (2) an optimal IB replica storage scheme, and (3) an adaptive and robust multi-resolution-based IB replica selection and transmission method. The experimental results show that the performance of our proposed UMIT method is both efficient and effective, minimizing the response time by decreasing the network transmission cost.

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Notes

  1. Strictly speaking, the professional preference refers to the organ(s) that a physician is specialized (or interested) in.

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Acknowledgments

The authors would like to thank the editors and anonymous reviewers for their helpful comments. This work is partially supported by the Program of the National Natural Science Foundation of China under Grant Nos. 61272188, 61540064, 61379075; the Ministry of Education of Humanities and Social Sciences Project under Grant No. 14YJCZH235; the “Qianjiang Talent” Project of Zhejiang Province under Grant No. QJD1402017; the National Science & Technology Pillar Program under Grant No. 2014BAK14B01; and the Program of Natural Science Foundation for Distinguished Young Scholars of Zhejiang Province.

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Authors and Affiliations

  1. College of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, People’s Republic of China

    Yi Zhuang

  2. Hangzhou First People’s Hospital, Hangzhou, People’s Republic of China

    Nan Jiang

  3. Department of Computer Science, City University of Hong Kong, Hong Kong, People’s Republic of China

    Qing Li

  4. School of Computer, Hangzhou Dianzi University, Hangzhou, People’s Republic of China

    Hua Hu

  5. Faculty of Education, The University of Hong Kong, Hong Kong, People’s Republic of China

    Dickson K. W. Chiu

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  1. Yi Zhuang
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  2. Nan Jiang
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  3. Qing Li
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  4. Hua Hu
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  5. Dickson K. W. Chiu
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Correspondence to Yi Zhuang.

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Communicated by B. Prabhakaran.

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Zhuang, Y., Jiang, N., Li, Q. et al. Towards professionally user-adaptive large medical image transmission processing in mobile telemedicine systems. Multimedia Systems 24, 123–145 (2018). https://doi.org/10.1007/s00530-016-0526-5

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